TRON gGmbH - Translational Oncology at Johannes Gutenberg-University Medical Center gGmbH ; Langenbeckstr; Mainz, Germany ; University Medical Center of the Johannes Gutenberg-University Mainz ; Mainz, Germany.
TRON gGmbH - Translational Oncology at Johannes Gutenberg-University Medical Center gGmbH ; Langenbeckstr; Mainz, Germany.
Oncoimmunology. 2014 Aug 3;3(8):e954893. doi: 10.4161/21624011.2014.954893. eCollection 2014.
Cancer cell lines are a tremendous resource for cancer biology and therapy development. These multipurpose tools are commonly used to examine the genetic origin of cancers, to identify potential novel tumor targets, such as tumor antigens for vaccine devel-opment, and utilized to screen potential therapies in preclinical studies. Mutations, gene expression, and drug sensitivity have been determined for many cell lines using next-generation sequencing (NGS). However, the human leukocyte antigen (HLA) type and HLA expression of tumor cell lines, characterizations necessary for the development of cancer vaccines, have remained largely incomplete and, such information, when available, has been distributed in many publications. Here, we determine the 4-digit HLA type and HLA expression of 167 cancer and 10 non-cancer cell lines from publically available RNA-Seq data. We use standard NGS RNA-Seq short reads from "whole transcriptome" sequencing, map reads to known HLA types, and statistically determine HLA type, heterozygosity, and expression. First, we present previously unreported HLA Class I and II genotypes. Second, we determine HLA expression levels in each cancer cell line, providing insights into HLA downregulation and loss in cancer. Third, using these results, we provide a fundamental cell line "barcode" to track samples and prevent sample annotation swaps and contamination. Fourth, we integrate the cancer cell-line specific HLA types and HLA expression with available cell-line specific mutation information and existing HLA binding prediction algorithms to make a catalog of predicted antigenic mutations in each cell line. The compilation of our results are a fundamental resource for all researchers selecting specific cancer cell lines based on the HLA type and HLA expression, as well as for the development of immunotherapeutic tools for novel cancer treatment modalities.
癌细胞系是癌症生物学和治疗开发的宝贵资源。这些多用途工具常用于研究癌症的遗传起源,鉴定潜在的新型肿瘤靶标,如用于疫苗开发的肿瘤抗原,并用于筛选临床前研究中的潜在治疗方法。已经使用下一代测序 (NGS) 确定了许多细胞系的突变、基因表达和药物敏感性。然而,肿瘤细胞系的人类白细胞抗原 (HLA) 类型和 HLA 表达——这是癌症疫苗开发所必需的特征——在很大程度上仍然不完整,并且在可用时,此类信息已在许多出版物中进行了分发。在这里,我们从公开的 RNA-Seq 数据中确定了 167 种癌症和 10 种非癌细胞系的 4 位数字 HLA 类型和 HLA 表达。我们使用来自“全转录组”测序的标准 NGS RNA-Seq 短读序列,将读序列映射到已知的 HLA 类型,并通过统计学方法确定 HLA 类型、杂合性和表达。首先,我们展示了以前未报告的 HLA I 类和 II 类基因型。其次,我们确定了每个癌细胞系中的 HLA 表达水平,深入了解了 HLA 下调和丢失在癌症中的作用。第三,使用这些结果,我们提供了一个基本的细胞系“条码”,以跟踪样本并防止样本注释交换和污染。第四,我们将癌细胞系特异性 HLA 类型和 HLA 表达与可用的细胞系特异性突变信息和现有的 HLA 结合预测算法相结合,以制作每个细胞系中预测抗原突变的目录。我们的研究结果汇编为所有根据 HLA 类型和 HLA 表达选择特定癌细胞系的研究人员以及为新型癌症治疗模式的免疫治疗工具开发提供了基本资源。